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Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
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2D and 3D Angles-Only Target Tracking Based on Maximum Correntropy Kalman Filters.

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This study introduces new algorithms for angles-only target tracking in non-Gaussian environments. These methods improve accuracy by using a maximum correntropy criterion (MCC) framework, outperforming traditional estimators with impulsive noise.

Keywords:
Cauchy kernelGaussian kernelmaximum correntropy criterionnon Gaussian noisenonlinear filtering

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Area of Science:

  • Signal Processing
  • Estimation Theory
  • Robotics

Background:

  • Angles-only target tracking (AoT) is crucial for navigation and surveillance.
  • Conventional estimators struggle with non-Gaussian noise and outliers.
  • Impulsive noise degrades the performance of minimum mean square error (MMSE) estimators.

Purpose of the Study:

  • To develop robust estimation algorithms for AoT in non-Gaussian environments.
  • To address the limitations of MMSE estimators in the presence of outliers.
  • To introduce a maximum correntropy criterion (MCC) based framework for improved AoT accuracy.

Main Methods:

  • Developed three novel estimation algorithms: MC-UKF-CK, MC-NSKF-GK, and MC-NSKF-CK.
  • Utilized sigma point filters, including the unscented Kalman filter (UKF).
  • Employed Gaussian and Cauchy kernels within the MCC framework.

Main Results:

  • The proposed algorithms demonstrated superior estimation accuracy compared to conventional methods.
  • Evaluated performance using root-mean-square error (RMSE) in position and % track loss.
  • Simulations in 2D and 3D AoT scenarios confirmed improved robustness against non-Gaussian noise.

Conclusions:

  • The MCC-based framework provides a robust solution for AoT problems with non-Gaussian measurement noise.
  • The developed algorithms (MC-UKF-CK, MC-NSKF-GK, MC-NSKF-CK) offer enhanced accuracy and reliability.
  • This research advances AoT capabilities in challenging, real-world environments.